Automated Guided Vehicle Navigation Device and Method Thereof

2. The automated guided vehicle navigation device of claim 1, comprising a controller configured to automatically navigate the automated guided vehicle according to a real-time depth image data and a real-time color image data captured by the RGB-D camera, and the training result.

3. The automated guided vehicle navigation device of claim 2, wherein the controller obtains the accelerations, the moving speeds, the directions, the rotation angles and the moving distances, corresponding to the real-time depth image data, according to the real-time depth image data and the real-time color image data, and controls the automated guided vehicle, in real time, to move with the accelerations, the moving speeds, the directions, the rotation angles and the moving distances.

4. The automated guided vehicle navigation device of claim 3, wherein the controller determines one or more stop points of the target route according to the real-time color image data captured by the RGB-D camera and the training result.

5. The automated guided vehicle navigation device of claim 4, wherein the controller compares a similarity, between the real-time color image data captured by the RGB-D camera and a color image of any one of the stop points of the training result, with a predetermined threshold value in order to determine whether a current position is one of the stop points.

6. The automated guided vehicle navigation device of claim 1, wherein the automated guided vehicle is operated to move along the target route for several times.

7. The automated guided vehicle navigation device of claim 1, wherein the sensors comprises an inertial measurement unit configured to detect the acceleration, the moving speed, the direction and the rotation angle of the automated guided vehicle when the automated guided vehicle moves along each of the paths.

8. The automated guided vehicle navigation device of claim 1, wherein the sensors comprises a rotary encoder configured to detect the moving distance of the automated guided vehicle when the automated guided vehicle moves along each of the paths.

9. The automated guided vehicle navigation device of claim 1, wherein the sensors comprises an obstacle avoidance sensor configured to detect whether there is an obstacle in front of the automated guided vehicle.

10. The automated guided vehicle navigation device of claim 9, wherein the obstacle avoidance sensor is an ultrasonic sensor or an infrared sensor.

11. The automated guided vehicle navigation device of claim 1, wherein the machine learning model is a convolutional neural network model.

20. The automated guided vehicle navigation method of claim 19, wherein the obstacle avoidance sensor is an ultrasonic sensor or an infrared sensor.

21. The automated guided vehicle navigation method of claim 12, wherein the machine learning model is a convolutional neural network model.